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<br>Announced in 2016, Gym is an open-source Python library designed to facilitate the development of reinforcement knowing algorithms. It aimed to standardize how environments are defined in [AI](http://8.140.200.236:3000) research study, making published research more quickly reproducible [24] [144] while offering users with an easy user [interface](https://deadlocked.wiki) for connecting with these environments. In 2022, [pediascape.science](https://pediascape.science/wiki/User:BarrettMacNeil5) brand-new advancements of Gym have been moved to the library Gymnasium. [145] [146] |
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<br>Gym Retro<br> |
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<br>Released in 2018, Gym Retro is a platform for support knowing (RL) research study on computer game [147] utilizing RL algorithms and research study generalization. Prior RL research focused mainly on enhancing representatives to resolve single tasks. Gym Retro provides the capability to generalize in between video games with similar principles but different looks.<br> |
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<br>RoboSumo<br> |
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<br>Released in 2017, RoboSumo is a virtual world where humanoid metalearning robot agents initially do not have [knowledge](http://adbux.shop) of how to even walk, however are provided the [objectives](https://www.istorya.net) of discovering to move and to press the opposing representative out of the ring. [148] Through this adversarial learning process, the representatives discover how to adapt to changing conditions. When an agent is then removed from this virtual environment and positioned in a brand-new virtual environment with high winds, the agent braces to remain upright, [engel-und-waisen.de](http://www.engel-und-waisen.de/index.php/Benutzer:UtaCabrera5974) suggesting it had actually learned how to balance in a generalized way. [148] [149] OpenAI's Igor Mordatch argued that competition between representatives could develop an intelligence "arms race" that might increase an agent's capability to operate even outside the context of the competition. [148] |
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<br>OpenAI 5<br> |
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<br>OpenAI Five is a group of five OpenAI-curated bots utilized in the competitive five-on-five video game Dota 2, that find out to play against human gamers at a high ability level completely through trial-and-error algorithms. Before ending up being a group of 5, the very first public demonstration happened at The International 2017, the annual premiere champion competition for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live individually matchup. [150] [151] After the match, CTO Greg that the bot had actually discovered by playing against itself for two weeks of real time, and that the learning software was a step in the instructions of producing software that can handle complex tasks like a cosmetic surgeon. [152] [153] The system uses a form of reinforcement learning, as the bots discover with time by playing against themselves numerous times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives. [154] [155] [156] |
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<br>By June 2018, the ability of the bots expanded to play together as a complete group of 5, and they had the ability to beat teams of amateur and semi-professional players. [157] [154] [158] [159] At The International 2018, OpenAI Five played in two [exhibition matches](https://www.webthemes.ca) against expert gamers, however wound up losing both games. [160] [161] [162] In April 2019, OpenAI Five defeated OG, the reigning world champs of the video game at the time, 2:0 in a live exhibition match in San Francisco. [163] [164] The bots' last public look came later on that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those video games. [165] |
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<br>OpenAI 5's mechanisms in Dota 2's bot gamer reveals the challenges of [AI](https://kahps.org) systems in multiplayer online battle arena (MOBA) games and how OpenAI Five has demonstrated the usage of deep support learning (DRL) agents to attain superhuman competence in Dota 2 matches. [166] |
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<br>Dactyl<br> |
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<br>Developed in 2018, Dactyl utilizes maker learning to train a Shadow Hand, a human-like robotic hand, to control physical things. [167] It discovers completely in simulation utilizing the exact same RL algorithms and [training](https://swahilihome.tv) code as OpenAI Five. OpenAI dealt with the object orientation problem by utilizing domain randomization, a simulation method which exposes the student to a range of experiences instead of attempting to fit to truth. The set-up for Dactyl, aside from having motion tracking cams, also has RGB video [cameras](https://xn--9m1bq6p66gu3avit39e.com) to allow the robot to control an approximate object by seeing it. In 2018, OpenAI revealed that the system had the ability to control a cube and an octagonal prism. [168] |
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<br>In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot was able to resolve the puzzle 60% of the time. Objects like the Rubik's Cube present complicated physics that is harder to design. OpenAI did this by enhancing the robustness of Dactyl to perturbations by utilizing Automatic Domain Randomization (ADR), a simulation technique of generating progressively harder environments. ADR varies from manual domain randomization by not requiring a human to specify randomization ranges. [169] |
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<br>API<br> |
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<br>In June 2020, OpenAI revealed a multi-purpose API which it said was "for accessing new [AI](http://47.90.83.132:3000) designs developed by OpenAI" to let designers contact it for "any English language [AI](http://119.29.169.157:8081) task". [170] [171] |
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<br>Text generation<br> |
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<br>The business has promoted generative pretrained transformers (GPT). [172] |
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<br>OpenAI's original GPT model ("GPT-1")<br> |
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<br>The original paper on generative pre-training of a [transformer-based language](https://www.sparrowjob.com) design was composed by Alec Radford and his colleagues, and [released](https://93.177.65.216) in preprint on OpenAI's website on June 11, 2018. [173] It demonstrated how a generative design of language could obtain world understanding and process long-range reliances by pre-training on a [varied corpus](https://placementug.com) with long stretches of contiguous text.<br> |
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<br>GPT-2<br> |
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<br>Generative Pre-trained Transformer 2 ("GPT-2") is a not being watched transformer language design and the follower to OpenAI's initial GPT design ("GPT-1"). GPT-2 was revealed in February 2019, with just restricted demonstrative variations at first released to the public. The full variation of GPT-2 was not instantly launched due to issue about prospective misuse, including applications for [composing](https://git.li-yo.ts.net) fake news. [174] Some experts revealed uncertainty that GPT-2 postured a considerable danger.<br> |
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<br>In response to GPT-2, the Allen Institute for [Artificial Intelligence](https://easterntalent.eu) responded with a tool to [discover](https://git.songyuchao.cn) "neural fake news". [175] Other scientists, such as Jeremy Howard, warned of "the innovation to absolutely fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would hush all other speech and be impossible to filter". [176] In November 2019, OpenAI launched the total variation of the GPT-2 language design. [177] Several websites host interactive demonstrations of various circumstances of GPT-2 and other transformer models. [178] [179] [180] |
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<br>GPT-2's authors argue without supervision language designs to be general-purpose learners, illustrated by GPT-2 attaining modern accuracy and [perplexity](https://linuxreviews.org) on 7 of 8 zero-shot tasks (i.e. the design was not additional trained on any task-specific input-output examples).<br> |
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<br>The corpus it was [trained](https://meeting2up.it) on, called WebText, contains slightly 40 gigabytes of text from URLs shared in [Reddit submissions](http://118.31.167.22813000) with at least 3 upvotes. It prevents certain concerns encoding vocabulary with word tokens by utilizing byte pair encoding. This allows representing any string of characters by encoding both private characters and multiple-character tokens. [181] |
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<br>GPT-3<br> |
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<br>First explained in May 2020, Generative Pre-trained [a] Transformer 3 (GPT-3) is an unsupervised transformer language design and the successor to GPT-2. [182] [183] [184] OpenAI specified that the complete variation of GPT-3 contained 175 billion criteria, [184] two orders of magnitude bigger than the 1.5 billion [185] in the full version of GPT-2 (although GPT-3 designs with as few as 125 million parameters were likewise trained). [186] |
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<br>OpenAI specified that GPT-3 [succeeded](https://www.majalat2030.com) at certain "meta-learning" jobs and might generalize the function of a [single input-output](http://gitlab.code-nav.cn) pair. The GPT-3 release paper gave examples of translation and cross-linguistic transfer learning between English and Romanian, and between English and German. [184] |
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<br>GPT-3 drastically enhanced benchmark outcomes over GPT-2. OpenAI warned that such scaling-up of language models could be approaching or experiencing the basic capability constraints of predictive language models. [187] Pre-training GPT-3 needed numerous thousand petaflop/s-days [b] of calculate, compared to 10s of petaflop/s-days for the full GPT-2 design. [184] Like its predecessor, [174] the GPT-3 trained model was not right away released to the public for concerns of possible abuse, although OpenAI prepared to allow gain access to through a [paid cloud](https://huconnect.org) API after a two-month free private beta that began in June 2020. [170] [189] |
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<br>On September 23, 2020, GPT-3 was licensed specifically to Microsoft. [190] [191] |
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<br>Codex<br> |
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<br>Announced in mid-2021, Codex is a descendant of GPT-3 that has actually additionally been trained on code from 54 million GitHub repositories, [192] [193] and is the [AI](http://git.setech.ltd:8300) powering the code autocompletion tool GitHub Copilot. [193] In August 2021, an API was released in [personal](https://addismarket.net) beta. [194] According to OpenAI, the design can create working code in over a lots programming languages, most efficiently in Python. [192] |
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<br>Several issues with problems, design flaws and security vulnerabilities were mentioned. [195] [196] |
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<br>GitHub Copilot has been implicated of discharging copyrighted code, with no author attribution or license. [197] |
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<br>OpenAI announced that they would cease support for Codex API on March 23, [setiathome.berkeley.edu](https://setiathome.berkeley.edu/view_profile.php?userid=11860868) 2023. [198] |
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<br>GPT-4<br> |
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<br>On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), efficient in accepting text or image inputs. [199] They announced that the upgraded innovation passed a simulated law school bar exam with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 might also read, evaluate or generate as much as 25,000 words of text, and write code in all significant programming languages. [200] |
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<br>Observers reported that the model of ChatGPT utilizing GPT-4 was an enhancement on the previous GPT-3.5-based iteration, [kigalilife.co.rw](https://kigalilife.co.rw/author/erickkidman/) with the caution that GPT-4 retained a few of the issues with earlier [modifications](https://granthers.com). [201] GPT-4 is likewise capable of taking images as input on ChatGPT. [202] OpenAI has declined to reveal different technical details and statistics about GPT-4, such as the precise size of the design. [203] |
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<br>GPT-4o<br> |
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<br>On May 13, 2024, OpenAI announced and released GPT-4o, which can process and create text, images and audio. [204] GPT-4o attained cutting [edge lead](http://szyg.work3000) to voice, multilingual, and vision criteria, setting brand-new records in audio speech recognition and translation. [205] [206] It scored 88.7% on the Massive Multitask Language Understanding (MMLU) benchmark compared to 86.5% by GPT-4. [207] |
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<br>On July 18, 2024, OpenAI released GPT-4o mini, a smaller variation of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT user [interface](https://onsanmo.co.kr). Its [API costs](https://revinr.site) $0.15 per million [input tokens](https://kahps.org) and $0.60 per million output tokens, compared to $5 and $15 respectively for GPT-4o. OpenAI anticipates it to be especially helpful for enterprises, startups and developers seeking to automate services with [AI](http://git.chaowebserver.com) representatives. [208] |
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<br>o1<br> |
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<br>On September 12, 2024, OpenAI launched the o1-preview and o1-mini models, which have been developed to take more time to consider their responses, resulting in greater precision. These models are especially reliable in science, [hb9lc.org](https://www.hb9lc.org/wiki/index.php/User:Margareta19E) coding, and thinking jobs, and were made available to ChatGPT Plus and Employee. [209] [210] In December 2024, o1-preview was changed by o1. [211] |
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<br>o3<br> |
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<br>On December 20, 2024, OpenAI revealed o3, the successor of the o1 reasoning design. OpenAI likewise revealed o3-mini, a lighter and quicker version of OpenAI o3. As of December 21, 2024, this design is not available for public use. According to OpenAI, they are testing o3 and o3-mini. [212] [213] Until January 10, 2025, [security](https://www.ifodea.com) and [higgledy-piggledy.xyz](https://higgledy-piggledy.xyz/index.php/User:MacFalls93386606) security researchers had the chance to obtain early access to these designs. [214] The model is called o3 rather than o2 to prevent confusion with telecoms companies O2. [215] |
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<br>Deep research<br> |
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<br>Deep research study is a representative developed by OpenAI, revealed on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform substantial web surfing, data analysis, and synthesis, [delivering detailed](https://chhng.com) reports within a timeframe of 5 to thirty minutes. [216] With browsing and Python tools allowed, it reached an accuracy of 26.6 percent on HLE (Humanity's Last Exam) criteria. [120] |
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<br>Image classification<br> |
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<br>CLIP<br> |
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<br>Revealed in 2021, CLIP (Contrastive Language-Image Pre-training) is a model that is trained to evaluate the semantic resemblance in between text and images. It can especially be used for image category. [217] |
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<br>Text-to-image<br> |
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<br>DALL-E<br> |
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<br>Revealed in 2021, DALL-E is a Transformer design that develops images from textual descriptions. [218] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural [language](http://119.167.221.1460000) inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and [produce matching](https://git.brass.host) images. It can develop images of reasonable items ("a stained-glass window with an image of a blue strawberry") along with objects that do not exist in truth ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.<br> |
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<br>DALL-E 2<br> |
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<br>In April 2022, OpenAI announced DALL-E 2, an upgraded version of the design with more practical outcomes. [219] In December 2022, OpenAI released on GitHub software for Point-E, a brand-new fundamental system for converting a [text description](http://www.lebelleclinic.com) into a 3-dimensional design. [220] |
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<br>DALL-E 3<br> |
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<br>In September 2023, OpenAI announced DALL-E 3, a more powerful design much better able to generate images from [complex descriptions](https://joinwood.co.kr) without manual prompt engineering and render complicated details like hands and text. [221] It was launched to the general public as a ChatGPT Plus feature in October. [222] |
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<br>Text-to-video<br> |
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<br>Sora<br> |
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<br>Sora is a text-to-video design that can create videos based upon short detailed triggers [223] in addition to extend existing videos forwards or backwards in time. [224] It can produce videos with resolution up to 1920x1080 or 1080x1920. The optimum length of generated videos is unidentified.<br> |
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<br>Sora's advancement team named it after the Japanese word for "sky", to signify its "unlimited innovative capacity". [223] Sora's innovation is an adaptation of the technology behind the DALL · E 3 text-to-image model. [225] OpenAI trained the system using publicly-available videos as well as copyrighted videos accredited for that function, however did not expose the number or the precise sources of the videos. [223] |
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<br>OpenAI showed some Sora-created high-definition videos to the public on February 15, 2024, stating that it might generate videos approximately one minute long. It likewise shared a technical report highlighting the methods used to train the design, and the [design's capabilities](http://git.nikmaos.ru). [225] It acknowledged some of its imperfections, consisting of battles simulating complicated physics. [226] Will Douglas Heaven of the MIT Technology Review called the presentation videos "outstanding", however noted that they should have been cherry-picked and may not represent Sora's common output. [225] |
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<br>Despite uncertainty from some academic leaders following Sora's public demonstration, noteworthy entertainment-industry figures have actually revealed significant interest in the innovation's capacity. In an interview, actor/filmmaker Tyler Perry expressed his astonishment at the innovation's capability to generate reasonable video from text descriptions, mentioning its possible to revolutionize storytelling and material creation. He said that his excitement about Sora's possibilities was so strong that he had actually decided to pause prepare for broadening his Atlanta-based motion picture studio. [227] |
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<br>Speech-to-text<br> |
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<br>Whisper<br> |
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<br>Released in 2022, Whisper is a general-purpose speech acknowledgment model. [228] It is trained on a big dataset of varied audio and is also a multi-task model that can carry out multilingual speech recognition as well as speech translation and language identification. [229] |
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<br>Music generation<br> |
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<br>MuseNet<br> |
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<br>Released in 2019, MuseNet is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate songs with 10 instruments in 15 designs. According to The Verge, a song produced by MuseNet tends to begin fairly but then fall under chaos the longer it plays. [230] [231] In popular culture, [preliminary applications](https://voyostars.com) of this tool were used as early as 2020 for the internet mental [thriller](https://www.app.telegraphyx.ru) Ben Drowned to produce music for the titular character. [232] [233] |
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<br>Jukebox<br> |
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<br>Released in 2020, Jukebox is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a category, artist, and a bit of lyrics and outputs tune samples. OpenAI stated the tunes "show local musical coherence [and] follow conventional chord patterns" but acknowledged that the tunes do not have "familiar bigger musical structures such as choruses that duplicate" which "there is a substantial gap" between Jukebox and human-generated music. The Verge stated "It's technologically excellent, even if the outcomes seem like mushy variations of tunes that may feel familiar", while Business Insider specified "surprisingly, some of the resulting tunes are catchy and sound legitimate". [234] [235] [236] |
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<br>Interface<br> |
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<br>Debate Game<br> |
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<br>In 2018, OpenAI launched the Debate Game, which teaches makers to discuss toy issues in front of a human judge. The purpose is to research study whether such a method might assist in auditing [AI](https://handsfarmers.fr) choices and in developing explainable [AI](https://findspkjob.com). [237] [238] |
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<br>Microscope<br> |
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<br>[Released](https://gitlab.iue.fh-kiel.de) in 2020, Microscope [239] is a collection of visualizations of every [substantial layer](https://git.pleasantprogrammer.com) and nerve cell of 8 neural network designs which are typically studied in interpretability. [240] Microscope was developed to evaluate the features that form inside these neural networks easily. The models included are AlexNet, VGG-19, various variations of Inception, and various variations of CLIP Resnet. [241] |
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<br>ChatGPT<br> |
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<br>Launched in November 2022, ChatGPT is an expert system tool constructed on top of GPT-3 that offers a conversational user interface that enables users to ask questions in natural language. The system then reacts with an answer within seconds.<br> |
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